A computer system with one or more graphics processing units (GPUs) may exhibit superior graphics capabilities, such as the ability to render high-resolution and/or three-dimensional video in real time. Each GPU installed in the system may include numerous processing cores, with each core capable of executing a different software thread. As such, each GPU is natively configured to enact parallel processing, where, for example, different software threads may be tasked with rendering different portions of an image, and/or different image frames in a video sequence. Parallel processing in a GPU may also provide graphics-rendering or other computing services to a plurality of concurrent processes. In computer systems equipped with a plurality of GPUs, an even greater degree of parallel processing may be available.
Nevertheless, not every computer system can support parallel processing with advanced, multi-core GPUs. Every GPU installed in a computer system contributes significantly to the size, cost, complexity, and power consumption of that system. Accordingly, portable computing devices such as smartphones, tablets, and even laptops may not be capable of high-performance graphics rendering or parallel computing in the manner of a desktop or workstation, for example. Furthermore, the act of mapping a large number of graphics-consumer processes to a large number of GPUs via a state-of-the-art driver layer is itself a complex task, the complexity increasing both with the number of computing processes and with the number of GPUs.